AWS Big Data

OCTOBER 30, 2024

Amazon DataZone recently announced the expansion of data analysis and visualization options for your project-subscribed data within Amazon DataZone using the Amazon Athena JDBC driver. Joel has led data transformation projects on fraud analytics, claims automation, and Master Data Management.

Analytics 119

Analytics Visualization Data Governance Data-driven 119

datapine

SEPTEMBER 29, 2022

However, with all good things comes many challenges and businesses often struggle with managing their information in the correct way. Oftentimes, the data being collected and used is incomplete or damaged, leading to many other issues that can considerably harm the company. Enters data quality management.

Data Quality 241

Data Quality Metrics Data-driven Management 241

datapine

MAY 2, 2023

To work effectively, big data requires a large amount of high-quality information sources. Where is all of that data going to come from? Proactivity: Another key benefit of big data in the logistics industry is that it encourages informed decision-making and proactivity.

Big Data 275

Big Data Internet of Things Cost-Benefit Optimization 275

AWS Big Data

DECEMBER 20, 2024

Your generated jobs can use a variety of data transformations, including filters, projections, unions, joins, and aggregations, giving you the flexibility to handle complex data processing requirements. In this post, we discuss how Amazon Q data integration transforms ETL workflow development.

Data Integration 105

Data Integration Visualization Data Processing Big Data 105

Wayne Yaddow

FEBRUARY 26, 2025

AI is transforming how senior data engineers and data scientists validate data transformations and conversions. Artificial intelligence-based verification approaches aid in the detection of anomalies, the enforcement of data integrity, and the optimization of pipelines for improved efficiency.

Data Transformation 52

Data Transformation Testing Data-driven Data Quality 52

DataKitchen

NOVEMBER 10, 2023

Extrinsic Control Deficit: Many of these changes stem from tools and processes beyond the immediate control of the data team. Unregulated ETL/ELT Processes: The absence of stringent data quality tests in ETL (Extract, Transform, Load) or ELT (Extract, Load, Transform) processes further exacerbates the problem.

Data Quality 136

Data Quality Testing Data Lake Data Integration 136

CIO Business Intelligence

APRIL 8, 2025

As data-centric AI, automated metadata management and privacy-aware data sharing mature, the opportunity to embed data quality into the enterprises core has never been more significant. Data lives across siloed systems ERP, CRM, cloud platforms, spreadsheets with little integration or consistency. Synthetic data.

Data Quality 102

Data Quality Data-driven Key Performance Indicator Metadata 102

DataKitchen

JULY 27, 2023

Here are a few examples that we have seen of how this can be done: Batch ETL with Azure Data Factory and Azure Databricks: In this pattern, Azure Data Factory is used to orchestrate and schedule batch ETL processes. Azure Blob Storage serves as the data lake to store raw data. Azure Machine Learning).

Machine Learning 130

Machine Learning Cost-Benefit Data Transformation Testing 130

AWS Big Data

NOVEMBER 9, 2023

A modern data platform entails maintaining data across multiple layers, targeting diverse platform capabilities like high performance, ease of development, cost-effectiveness, and DataOps features such as CI/CD, lineage, and unit testing. It does this by helping teams handle the T in ETL (extract, transform, and load) processes.

Data Warehouse 126

Data Warehouse Testing Data Quality Reporting 126

DataKitchen

OCTOBER 5, 2022

DataOps Observability can help you ensure that your complex data pipelines and processes are accurate and that they deliver as designed. Observability also validates that your data transformations, models, and reports are performing as expected. to monitor your data operations. without replacing staff or systems?to

Testing 169

Testing Risk Data Processing Statistics 169

CIO Business Intelligence

OCTOBER 11, 2022

The new approach involved federating its vast and globally dispersed data repositories in the cloud with Amazon Web Services (AWS). Unifying its data within a centralized architecture allows AstraZeneca’s researchers to easily tag, search, share, transform, analyze, and govern petabytes of information at a scale unthinkable a decade ago. .

Machine Learning 145

Machine Learning Data Science Data-driven Testing 145

CIO Business Intelligence

JULY 5, 2022

What is the difference between business analytics and data analytics? Business analytics is a subset of data analytics. Data analytics is used across disciplines to find trends and solve problems using data mining , data cleansing, data transformation, data modeling, and more.

Business Analytics 136

Business Analytics Prescriptive Analytics Data mining Diagnostic Analytics 136

Jen Stirrup

SEPTEMBER 30, 2021

Before we dive in, let’s define strands of AI, Machine Learning and Data Science: Business intelligence (BI) leverages software and services to transform data into actionable insights that inform an organization’s strategic and tactical business decisions. Once the model has been trained, it will need to be tested.

Business Intelligence 135

Business Intelligence Data mining Machine Learning Testing 135

DataKitchen

OCTOBER 25, 2022

The space agency created and still uses “mission control” where many screens share detailed data about all aspects of a space flight. That shared information is the basis for monitoring mission status, making decisions and changes, and then communicating to all people involved. DataOps Observability Starts with Data Journeys.

Testing 130

Testing Data-driven Visualization Dashboards 130

Sisense

AUGUST 28, 2020

Keeping data quality high ensures that the insights your end-users pull are aligned with reality and can help them (and the company at large) make smarter, d ata-driven decisions , as well as pipe quality information to customer-facing apps. . All this contributes to your overall data integrity profile.

Data Integration 101

Data Integration Testing Data Quality Data-driven 101

AWS Big Data

JUNE 19, 2024

Amazon Redshift gives you more flexibility in how you apply data masking to protect sensitive information stored in SUPER columns containing semi-structured data. SELECT * FROM svv_attached_masking_policy; Now you can test that different users can see the same data masked differently based on their roles.

Data Warehouse 115

Data Warehouse Testing Sales Structured Data 115

CIO Business Intelligence

JANUARY 19, 2024

To qualify for the aCAP exam, you need a master’s degree and less than three years of related experience in data or analytics. The exam tests general knowledge of the platform and applies to multiple roles, including administrator, developer, data analyst, data engineer, data scientist, and system architect.

Data Science 126

Data Science Machine Learning Predictive Modeling Forecasting 126

Cloudera

DECEMBER 9, 2022

Developers need to onboard new data sources, chain multiple data transformation steps together, and explore data as it travels through the flow. The side panel is context-sensitive and instantly displays relevant configuration information as you navigate through your flow components.

Testing 100

Testing Cost-Benefit Interactive Visualization 100

AWS Big Data

AUGUST 1, 2024

However, you might face significant challenges when planning for a large-scale data warehouse migration. This will enable right-sizing the Redshift data warehouse to meet workload demands cost-effectively. Additional considerations – Factor in additional tasks beyond schema conversion.

Data Warehouse 115

Data Warehouse KPI Optimization Cost-Benefit 115

DataKitchen

OCTOBER 5, 2022

DataOps Observability can help you ensure that your complex data pipelines and processes are accurate and that they deliver as designed. Observability also validates that your data transformations, models, and reports are performing as expected. to monitor your data operations. without replacing staff or systems?to

Testing 130

Testing Risk Data Processing Statistics 130

AWS Big Data

DECEMBER 13, 2023

In addition to using native managed AWS services that BMS didn’t need to worry about upgrading, BMS was looking to offer an ETL service to non-technical business users that could visually compose data transformation workflows and seamlessly run them on the AWS Glue Apache Spark-based serverless data integration engine.

Metadata 111

Metadata Data Lake Visualization Data Transformation 111

AWS Big Data

OCTOBER 14, 2024

Writing SQL queries requires not just remembering the SQL syntax rules, but also knowledge of the tables metadata, which is data about table schemas, relationships among the tables, and possible column values. Can it also help write SQL queries? The answer is yes.

Metadata 105

Metadata Data Lake Modeling Data Warehouse 105

AWS Big Data

APRIL 12, 2023

We also share a Spark benchmark solution that suits all Amazon EMR deployment options, so you can replicate the process in your environment for your own performance test cases. The solution uses the TPC-DS dataset and unmodified data schema and table relationships, but derives queries from TPC-DS to support the SparkSQL test cases.

Testing 104

Testing Big Data Metadata Optimization 104

AWS Big Data

AUGUST 26, 2024

Duplicating data from a production database to a lower or lateral environment and masking personally identifiable information (PII) to comply with regulations enables development, testing, and reporting without impacting critical systems or exposing sensitive customer data. See AWS Glue: How it works for further details.

Visualization 116

Visualization Metadata Data Transformation Testing 116

AWS Big Data

AUGUST 9, 2024

As businesses strive to make informed decisions, the amount of data being generated and required for analysis is growing exponentially. This trend is no exception for Dafiti , an ecommerce company that recognizes the importance of using data to drive strategic decision-making processes.

Data Lake 111

Data Lake Analytics Data Warehouse Data-driven 111

Smart Data Collective

APRIL 29, 2020

The techniques for managing organisational data in a standardised approach that minimises inefficiency. Extraction, Transform, Load (ETL). The extraction of raw data, transforming to a suitable format for business needs, and loading into a data warehouse. Data transformation. Microsoft Azure.

Management 98

Management Data Warehouse Digital Transformation Dashboards 98

AWS Big Data

NOVEMBER 29, 2023

dbt is an open source, SQL-first templating engine that allows you to write repeatable and extensible data transforms in Python and SQL. dbt is predominantly used by data warehouses (such as Amazon Redshift ) customers who are looking to keep their data transform logic separate from storage and engine.

Data Lake 122

Data Lake Management Metrics Data Warehouse 122

AWS Big Data

NOVEMBER 15, 2023

For more information on this foundation, refer to A Detailed Overview of the Cost Intelligence Dashboard. Each CDH dataset has three processing layers: source (raw data), prepared (transformed data in Parquet), and semantic (combined datasets). Within each stage, it’s possible to create resources for storing actual data.

Analytics 111

Analytics Dashboards Metadata Data Warehouse 111

CIO Business Intelligence

JANUARY 9, 2023

Customers are increasingly demanding access to real-time data, and freight transportation provider Estes Express Lines is among the rising tide of enterprises overhauling their data operations to deliver it. At one point, I had 15 people on my data team and seven of them were engaged only in data analysis.”

Data Strategy 111

Data Strategy Strategy Data Governance Marketing 111

Cloudera

OCTOBER 11, 2021

Modak Nabu relies on a framework of “Botworks”, a series of micro-jobs to accomplish various data transformation steps from ingestion to profiling, and indexing. Cloudera Data Engineering within CDP provides : Fully managed Spark-on-Kubernetes service that hides the complexity running production DE workloads at scale.

Data Lake 95

Data Lake Cost-Benefit Data-driven Dashboards 95

AWS Big Data

JUNE 20, 2023

You can perform log analysis on these logs to understand users’ application behavior and patterns to make informed decisions. Analyzing VPC flow logs helps you understand how your applications are communicating over the VPC network and acts as a main source of information to the network in your VPC. Choose Create delivery stream.

Dashboards 98

Dashboards Visualization Metrics Data Transformation 98

AWS Big Data

OCTOBER 11, 2023

Traditionally, such a legacy call center analytics platform would be built on a relational database that stores data from streaming sources. Data transformations through stored procedures and use of materialized views to curate datasets and generate insights is a known pattern with relational databases.

Management 131

Management Metadata Analytics Dashboards 131

AWS Big Data

FEBRUARY 8, 2023

Overview of the dataset being used The dataset we use is mimicking a source that holds customer information. This source has a manual process of inserting and updating customer data, and this has led to multiple instances of non-unique customers being represented with duplicate records.

Data Quality 98

Data Quality Testing Data Warehouse Unstructured Data 98

Cloudera

OCTOBER 13, 2020

Predict – Data Engineering (Apache Spark). CDP Data Engineering (1) – a service purpose-built for data engineers focused on deploying and orchestrating data transformation using Spark at scale. 3) Data Visualization is in Tech Preview on AWS and Azure. New Services. Learn More, Keep in Touch.

Data Warehouse 97

Data Warehouse Machine Learning Visualization Data Lake 97

Sisense

AUGUST 6, 2020

Be sure test cases represent the diversity of app users. As an AI product manager, here are some important data-related questions you should ask yourself: What is the problem you’re trying to solve? What data transformations are needed from your data scientists to prepare the data? The perfect fit.

Management 95

Management Machine Learning Key Performance Indicator Cost-Benefit 95

AWS Big Data

MAY 25, 2023

Data transformation plays a pivotal role in providing the necessary data insights for businesses in any organization, small and large. To gain these insights, customers often perform ETL (extract, transform, and load) jobs from their source systems and output an enriched dataset.

Reporting 96

Reporting Metrics Optimization Data Lake 96

AWS Big Data

DECEMBER 21, 2023

The data products from the Business Vault and Data Mart stages are now available for consumers. smava decided to use Tableau for business intelligence, data visualization, and further analytics. The data transformations are managed with dbt to simplify the workflow governance and team collaboration.

Data Lake 115

Data Lake Data Warehouse Data-driven B2B 115